Ovarian cancer, because of its low cure rate, is responsible for 5% of all cancer deaths in women. It is estimated that ovarian cancer caused 12,180 deaths in the United States in 2006. The majority of ovarian cancer cases are detected at an advanced stage (with metastases present beyond the ovaries), when disease is rarely curable. However, although most patients with advanced disease die within 2 years of diagnosis, a subset of these patients develop a more chronic form of ovarian cancer and survive 5 years or more with treatment. It is possible that patients with indolent cancer should be monitored and treated differently from patients with rapidly progressing ovarian cancer. However, at this point, clinicians do not have the tools to predict the clinical course of disease. Using a newly developed expression tag oligonucleotide array comparative genomic hybridization (CGH) platform, we have recently identified 12 CGH segments associated with overall survival in patients with high-grade, advanced-stage serous adenocarcinoma of the ovary. We found that DNA copy numbers of 91 genes in the 12 CGH segments were significantly correlated with transcription levels of those genes as evaluated by transcriptional profiling of RNA isolated from the same set of microdissected tumor tissue samples. In an independent set of high-grade, advanced-stage serous adenocarcinoma specimens, validation studies on one of these genes-FGF1, located on 5q31-showed that mRNA copy number was significantly correlated with DNA copy number and protein expression levels and that both FGF1 mRNA and FGF1 protein levels were significantly associated with worse overall patient survival. These data suggest that the combination of array CGH and expression profiling can successfully identify genetic biomarkers with prognostic value. Our long-term goal is to develop a genetic prognostic model for high- grade, advanced-stage serous adenocarcinoma. We have 3 specific aims: (1) Verify the correlation between DNA copy number abnormalities and gene expression for genes located in the 12 CGH segments that are significantly associated with overall and progression free survival in patients with high-grade, advanced stage serous adenocarcinoma. (2) Perform further validation studies utilizing an independent set of samples obtained from patients entered on Gynecologic Oncology Group protocol 218 and develop a provisional genetic prognostic model for high-grade, advanced stage serous adenocarcinoma. (3) Validate the prognostic value of each candidate marker using genetically characterized ovarian cancer cell lines and orthotopic mouse models. We believe that our combination of array CGH and expression profiling will allow us to identify functionally significant markers that are associated with reduced survival duration. These markers could be used to detect aggressive cancers and stratify patients into prognostic groups;could serve as therapeutic targets;and could facilitate patient stratification for phase III clinical trials.

Public Health Relevance

Project Narrative The proposed studies seek to perform further validation studies on genes located in the 12 comparative genomic hybridization (CGH) segments that are significantly associated with progression free and overall survival in patients with high-grade advanced stage serous ovarian cancer using a large collection of clinical trial specimens. Validated genetic changes will be used to compare with those identified in other histological types of ovarian cancers. By combining with transcriptional profiling data, validated candidate genes will be used to develop a genetic prognostic model for the disease. We will focus on genes that are associated with worse overall and progression free survival and with chemoresistance for further functional studies. A panel of genetically characterized ovarian cancer cell lines and an orthotopic ovarian cancer mouse model will be used to further validate the prognostic value of each selected candidate marker.

National Institute of Health (NIH)
National Cancer Institute (NCI)
Research Project (R01)
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Cancer Genetics Study Section (CG)
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Kim, Kelly Y
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University of Texas MD Anderson Cancer Center
Other Health Professions
Other Domestic Higher Education
United States
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Yeung, Tsz-Lun; Leung, Cecilia S; Wong, Kwong-Kwok et al. (2017) ELF3 is a negative regulator of epithelial-mesenchymal transition in ovarian cancer cells. Oncotarget 8:16951-16963
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Yeung, Tsz-Lun; Leung, Cecilia S; Li, Fuhai et al. (2016) Targeting Stromal-Cancer Cell Crosstalk Networks in Ovarian Cancer Treatment. Biomolecules 6:3
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Wong, Kwong-Kwok; Izaguirre, Daisy I; Kwan, Suet-Yan et al. (2013) Poor survival with wild-type TP53 ovarian cancer? Gynecol Oncol 130:565-9

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